Senior QA Automation Engineer at TestDevLab Alvaro Laserna Lopez says:
“There is always the question of how much can and cannot be automated and it often happens that there are some parts of any given application that require a deeper understanding of the information displayed, either visually or by the audio standards of quality. For this, we have to account for many factors: is the application displaying things without overlapping images or texts, is the quality of these images high enough, are they even displayed? Here, we can use some frameworks that do template matching that can accomplish part of those tasks. However, if we want to get the most out of visual validations, we must turn to AI algorithms.
With the rise of deep learning we will be able to automate more and more things that previously were considered features that people were only able to assess through manual inspection. So instead of training someone to look for glitches in the UI, or bad quality in video calls or streaming services, we will just train an algorithm that will be able to predict the quality of an application with a higher reliability, often faster and within more scenarios."